Seeking the Holy Grail of RWE

Billion-dollar acquisitions tend to make a lot of noise. Markets react, competitors get jittery and share prices can spike or tumble.

When Roche bought Flatiron Health, a tech platform that captures and synthesizes structured and unstructured oncology data, for $1.9 billion back in February, it sent tremors throughout the healthcare industry.

The ripple effect cannot be chalked up to corporate muscle-flexing however. The deal sent an unequivocal message that the time has come to establish a regulatory-grade standard for real-world evidence.

Commenting on the tie-up, Roche’s CEO said, “This is an important step in our personalised healthcare strategy for Roche, as we believe that regulatory-grade real-world evidence is a key ingredient to accelerate the development of, and access to, new cancer treatments.”

But what exactly is a regulatory-grade standard and why is it regarded as the holy grail of real-world evidence?

“Regulatory-grade data are data that are of a sound enough quality that they can be used for regulatory authorities to make robust decisions,” says Jacqueline Law, Global Head, Real World Data Science, Roche/Genentech.

Flatiron defines regulatory-grade real-world data as data collected as part of a patient’s routine clinical care that has been carefully curated and can be used in a regulatory context, says Shane Woods, VP, Life Sciences at Flatiron Health. To meet regulatory-grade requirements, the data must meet be evaluated across the following criteria: 1) high quality, 2) complete, 3) transparent, 4) generalizable, 5) timely, and 6) scalable.

In this way, compiled metadata (a set of data that describes and gives information about other data) across these criteria accompanies each dataset, allowing stakeholders to assess their confidence level in a finding generated from real-world data, says Woods.

The Times They are A-Changin’
The need for regulatory-grade RWD is emerging from a thirst for evidence across the healthcare environment, says Law.

“There is a growing demand of evidence to support R&D given the exploding pipeline, especially in oncology where there is also a countless number of potential combinations and an increasing number of molecularly-defined patient sub-populations.”

The ongoing move to value-based healthcare models, where evidence is required to demonstrate the quality of treatments in real-world settings, can also be a key driver, she says.

Most of the evidence used for R&D has been generated from clinical trials, however, only 5 percent of patients participate in clinical trials.

Woods agrees that randomized clinical trials are no match for the increasing number of questions that researchers are looking to ask.

This includes the FDA’s commissioner Scott Gottlieb, who said in a recent statement: ‘The FDA, along with others, sometimes benefit from more information than these trials can provide about how medical products are used in medical practice.’

The problem is particularly pronounced in oncology given the pace of development, says Woods. RCTs are expensive, do not often represent the entire patient population who will be using the drug and can take years to complete.

This is where real-world data steps in. “We believe that RWE can supplement traditional trials data and, in some instances, replace a trial all together. For example, often traditional clinical trial approaches will have limited or lack clinical evidence in a broad population because of the narrower patient population that can participate – given patient inclusion and exclusion criteria – ultimately creating knowledge gaps where we have a need to understand how these therapies will work in the real world.”

In addition, regulatory-grade RWD could step in where the target patient population is too small for randomized clinical trials to be feasible, says Law.

“The very conduct of clinical trials, their design, their execution and the skill set required to develop drugs through the phases themselves would likely see a seismic shift. How we think of drug development will fundamentally change.”

The squeeze from payers and regulatory bodies to understand the generalizability of clinical trial data is in part because patients that have comorbid illnesses are on different medications and have different levels of compliance to treatment that’s being prescribed to them over different durations of time,” says Chatterjee.

The cost of care spirals as the number of drugs available to doctors, patients and payers multiplies, he says. Establishing a standard for RWE could help contain all of this.

Making sense of data and attempting to carve out a universal standard is nothing new for the industry, the difference now is that the “inflection on the technology curve has gotten us to the point where we can access very large quantities of data for gigantic amounts of information,” says Chatterjee.

Software now enables us to talk to different databases and to combine information in ways that allow us to make meaningful comparisons and analysis’, he adds.

Are we there yet?
The industry’s movements are encouraging but we still have work to do.

“While Flatiron has the proprietary technology and technicians to extract both structured and unstructured data from the EHR, the next challenge industry-wide will be to continue to expand the way in which real-world data can be used, not just for, say, fulfilling post marketing commitments or label expansion, but also as an external control arm for certain clinical trials,” says Woods.

If real-world data can be incorporated in the trial design as an external control arm, it could potentially supplement or entirely replace the need for a traditional control arm in a clinical trial, increasing the likelihood that patients in clinical trials will access innovative experimental therapies, he says.

Law acknowledges the industry still needs to roll up its sleeves. “Real-world data is often criticized for being incomplete and poor quality; there's a lot of work to raise the bar to the regulatory-grade quality level.”

She is encouraged by Flatiron’s work with Roche and others in the healthcare system to get regulatory-grade RWD off the ground but calls for much more collaboration.

“This must be a multi-stakeholder industry-wide collaboration to move this forward,” she says.

Yay or nay?
Regulators appear to be singing from the same hymn sheet.

The FDA is actively working towards creating industry standards for RWE, as mandated by the 21st Century Cures Act signed by former president Barack Obama in December 2016. The idea is to enable the use of RWE to support approvals of new indications, label expansion, post-marketing follow-up and much more.

Flatiron is collaborating with the FDA and other industry stakeholders to articulate standards and guidance around the application, data quality requirements (including the development of real-world endpoints validated against those collected in a traditional clinical trial setting), and use of RWE for retrospective and prospective research, particularly as it relates to regulatory decision-making.

In parallel, it’s also the engagement and actual application of RWE with regulators and health authorities that’s helping shape development of the standards and guidance themselves.

The former commissioner, Robert Califf, has also noted that the current deficit in evidence has become particularly acute for the FDA, stating that numerous areas lack the vital evidence needed to support definitive regulatory determinations.

“Given the evidence demands, FDA is particularly keen to explore how and when high-quality, credible RWE can inform regulatory decisions; similarly, we know that agencies outside of the US, such as NICE and the European Medicines Agency, are very much open to the idea of using regulatory-grade real-world data to make decisions,” says Woods.

Law can testify. “We [Roche] have discussions with the EMA and they are very interested in exploring the use of real-world data to support regulatory decisions, and there are various initiatives with industry partners and collaborative consortiums that are looking at how we can advance real-world data to support regulatory decision-making.”

Flatiron’s biggest learning curve from working with regulators, in particular the FDA, is that they are keen to understand the boundaries of what is possible with RWE, says Woods.

“They want to innovate, and it is up to us - the industry - to collaborate with them to ensure full transparency into the process of generating regulatory-grade real world data. This ties back to my earlier point about the importance of generating and sharing the metadata to describe the dataset itself.”

Anjan Chatterjee’s views are his own and do not represent the views of Boehringer Ingelheim.